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The accumulated technologies and practices of general computer science and software engineering have failed to impact the productivity gridlock in scientific programming. Resolving this “productivity crisis” will require that the scientific programming communities relax their unending pursuit of 100% resource utilization and that the computer science and software engineering communities understand and appreciate the difference in goals between the two domains. Lessons learned from the great strides in general computing can then be adapted to scientific computing.